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The Love Equation: Computational Modeling of Romantic Relationships in French Classical Drama

Authors Folgert Karsdorp, Mike Kestemont, Christof Schöch, Antal van den Bosch

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  • French drama
  • social relations
  • neural network
  • representation learning

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Abstract

We report on building a computational model of romantic relationships in a corpus of historical literary texts. We frame this task as a ranking problem in which, for a given character, we try to assign the highest rank to the character with whom (s)he is most likely to be romantically involved. As data we use a publicly available corpus of French 17th and 18th century plays (http://www.theatre-classique.fr/) which is well suited for this type of analysis because of the rich markup it provides (e.g. indications of characters speaking). We focus on distributional, so-called second-order features, which capture how speakers are contextually embedded in the texts. At a mean reciprocal rate (MRR) of 0.9 and MRR@1 of 0.81, our results are encouraging, suggesting that this approach might be successfully extended to other forms of social interactions in literature, such as antagonism or social power relations.

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Folgert Karsdorp, Mike Kestemont, Christof Schöch, and Antal van den Bosch. The Love Equation: Computational Modeling of Romantic Relationships in French Classical Drama. In 6th Workshop on Computational Models of Narrative (CMN 2015). Open Access Series in Informatics (OASIcs), Volume 45, pp. 98-107, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015) https://doi.org/10.4230/OASIcs.CMN.2015.98

Author Details

Folgert Karsdorp
Mike Kestemont
Christof Schöch
Antal van den Bosch

References

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